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Race data project shows signs of promise

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Ottawa Citizen

Publishing date:

February 22, 2014 • 3 minute read

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In a settlement agreement between the Ottawa Police Services Board and the Ontario Human Rights Commission, and as part of a strategic operational plan to ensure bias-free policing, the police service agreed to collect race-based data. The Traffic Stop Race Data Collection Project began on June 27, 2013. Under the agreement, at traffic stops officers are required to record their perception of a driver’s race. This project is now halfway through its two-year mandate.

On Feb. 6, a community consultation was held, to provide a project update, solicit residents’ feedback on key project accomplishments to date and communicate plans for analyzing the study data and report. Several important insights emerged from the three-hour meeting.

In the seven months, the project has recorded approximately 35,000 traffic stops. Strong compliance rates — 80 to 90 per cent — were noted with requests for information recorded in the eight data fields (such as reason for the stop, driver’s information and outcome of the stop). The reported data were of a significantly robust quality, indicating a likelihood of “accurate” findings. Additional quality-assurance measures, such as ongoing training for all members of the police service, including new recruits and senior management, have been identified and will contribute to the integrity of the data-collection process.

Round- and small-table chats offered new perspectives on the project’s implementation. Countering skepticism, front-line officers indicated a desire to collect meaningful data to help them do their job better. However, operational and practical constraints such as placement and data collection tools have made this difficult. Preliminary evidence from police ride-alongs seemed to reveal officers’ inability to discern the race of drivers from within their own vehicles, because of the distance between them and the drivers. If valid, the implication of this — that police are unlikely to engage in racial profiling when they cannot see the drivers clearly — would turn conventional traffic-stop thinking upside down. Nevertheless, it would not address the kind of profiling that results from stops of racialized groups, such as the phenomenon of “driving while black.”

The traffic-stop race data collection team seemed cognizant that no research is perfect, and showed good faith by candidly acknowledging the project’s limitations, including incomplete traffic-stop data, pre-emption of officers from routine traffic stops due to emergency calls, ongoing need for training, and occasional computer glitches. In doing so, they demonstrated their commitment to strengthening community buy-in to the goals and promise of the initiative.

Several areas of contention remain, which seem unlikely to be resolved during the project’s lifespan. The project’s focus on traffic stops discounts other important settings where racial profiling occurs, according to evidence-based research. This important issue could have implications for police administration, research and policy relating to racial profiling. Another concern was how good data based on police perception — particularly an officer’s perception of a driver’s race — could be.

The question raises an interesting paradox. Members of racialized groups are asked to have faith and confidence in a police service that first denied, then acknowledged and later conceded to a partial racial-profiling settlement in the summer of 2010. Why should they now be compelled to trust police perceptions of them? Such a request may seem a tall order. Still, progress must not be masked by this painful reality.

The project must make an effort to integrate racialized youth; they have been glaringly absent in the project. Equally, in support of the community-led philosophy of the initiative, affected communities should be more significantly represented on the panels. Confusion still remains over how the communities will work together with the police and research team to prepare the final report. Without access to physical data and the training to analyze such data, the communities cannot effectively engage in or contribute to this activity.

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Finally, a community-wide conversation must begin in earnest regarding the use of the data being collected. How can it aid police procedures? How, if at all, can it inform the dynamics of racial profiling during pedestrian stops?

The police must be commended for their leadership on this matter. Nevertheless, a continuing, collective effort must be put toward gaining a better insight into the occurrence of racial profiling in police traffic-stop practices.

Sulaimon Giwa is a PhD candidate in the Faculty of Liberal Arts and Professional Studies, School of Social Work, at York University. He was the coordinator for Community Policing: A Shared Responsibility, a project that received federal funding from the Department of Canadian Heritage to address racism and racial profiling in policing in Ottawa. He can be reached by email at sol.giwa@gmail.com

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